Integrating mathematical models of cellular differentiation into current frameworks

Understanding the evolution of individuality, and the evolution of multicellularity, requires an understanding of why the unit of adaptation shifts from the lower level (such as a cell) to the higher level (such as a cell group, or multicellular organism). The evolutionary transition in individuality (ETI) framework hypothesizes that groups of individuals evolve into a new higher-level individual through processes involving five factors: cooperation and conflict, life history trade-offs, multi-level selection, division of labor, and the decoupling of fitness at the level of the group from the level of the cell.

In recent years, there have been many mathematical models published on the evolution of multicellularity and the evolution of division of labor. Written by research groups that then left the field of the evolution of multicellularity, many of these models were relatively disconnected from the prevailing literature, including the ETI framework. For this project, we reviewed the theory of ETIs in an attempt to relate recent theoretical work to the ETI framework.

There are two especially relevant conclusions of this work. First, in order for mathematical models to provide relevant predictions, they must incorporate basic life history issues. Obviously, some generalization is necessary and desirable for a mathematical model; however, when a model forgoes basic aspects of the life history (such as viability and reproduction), it is difficult to evaluate a model’s predictions in specific cases. We found several cases of this in the current literature. For example, Ispolatov & Doebeli (Ispolatov et al. 2011) model the evolution of multicellularity with cyanobacteria in mind. They model an aggregative process in which all cells reproduce. Given that multicellular cyanobacteria do not develop via aggregation, nor do all cells reproduce (Kumar et al. 2010; Muro-Pastor and Hess 2012), it is difficult to apply the predictions of Ispolatov & Doebeli (Ispolatov et al. 2011) even to the case they are considering. While the amount of life history details included in the model vary with the model’s intentions, some appreciation of life history is critical in order to build and apply the model.

Second, fitness components must be further connected to empirical work. Previous work (Michod et al. 2005; Michod 2006, 2007) modeled cellular differentiation as the specialization on fitness components, viability and reproduction. While the relationship of germ cells to reproduction is easily tractable, this work was agnostic to how somatic cells influenced viability. Recent models are also agnostic to how lower level units (e.g., cells) relate to fitness components. For example, this is seen in Van Dyken & Wade (Van Dyken and Wade 2012a,b) which assumed units of energy somehow relate to viability and fecundity as well as Rueffler et al. (Rueffler et al. 2012), which modeled units specializing on some tasks which traded off which each other. This conclusion of our review motivates several of my other research projects, which investigate how somatic cells influence viability.